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Day 32 Range Sensor Models 11/13/2018.

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Presentation on theme: "Day 32 Range Sensor Models 11/13/2018."— Presentation transcript:

1 Day 32 Range Sensor Models 11/13/2018

2 Range Sensors range sensors measure the distance between the robot and the sensed object(s) bearing measurement can be obtained by rotating the sensor or using multiple sensors arranged on a circular arc many non-vision based sensors can be modeled by measuring the distance along a beam or cone 11/13/2018

3 Infra-red Range Sensor
uses an IR LED and a linear CCD array to triangulate distances object object angle increases as distance increases Sharp GP2Y0A21YK0F data sheet 11/13/2018

4 Infra-red Range Sensor
has a minimum and maximum distance changes depending on the model but range is on the order of a few centimeters to a few meters inexpensive (less than $20) measurements affected by the material properties of the object but less sensitive to the orientation of the reflecting surface low accuracy 11/13/2018

5 Ultrasound Range Sensors
ultrasound is sound above the upper limit of human hearing (approximately 20,000 Hz) inexpensive ultrasonic transducers are essentially ceramic discs that vibrate at ultrasonic frequencies operate via the piezoelectric effect an applied external electric field causes a small change in the physical dimensions conversely, an applied stress will induce a small electric field 11/13/2018

6 Ultrasound Range Sensors
basic idea of operation is simple transducer emits a short pulse of ultrasound receiver listens for echo time elapsed between pulse and echo is proportional to twice the distance to the object 11/13/2018

7 Ultrasound Range Sensors
speed of sound in air is given approximately by where T is temperature in Celsius humidity affects c modern electronics can easily measure elapsed time with sufficient precision to obtain good distance resolution 11/13/2018

8 Ultrasound Range Sensors
most materials are specular reflectors of ultrasound Strickland and King, “Characteristics of Ultrasonic Ranging Sensors in an Underground Environment” 11/13/2018

9 Ultrasound Range Sensors
multiple reflections produce erroneous distance measurements Strickland and King, “Characteristics of Ultrasonic Ranging Sensors in an Underground Environment” 11/13/2018

10 Ultrasound Range Sensors
unfocussed ultrasound transducers have a wide beam pattern with significant side lobes Cao and Borenstein, “Experimental Characterization of Polaroid Ultrasonic Sensors in Single and Phased Array Configuration” 11/13/2018

11 Ultrasound Range Sensors
beamwidth + side lobes leads to spurious measurements Cao and Borenstein, “Experimental Characterization of Polaroid Ultrasonic Sensors in Single and Phased Array Configuration” 11/13/2018

12 LIDAR light detection and ranging commercial range finder disassembled
11/13/2018

13 LIDAR for time of flight sensor
speed of light 1 ns = 150 mm 100 ps = 15 mm 10 ps = 1.5 mm typical angular resolution below 1 degree typical errors on the order of 10 cm or less cost > $1,000 11/13/2018

14 Beam Models of Range Finders
given the map and the robot’s location, find the probability density that the range finder detects an object at a distance along a beam the k is here because range sensors typically return many measurements at one time; e.g., the sensor might return a full 360 degree scan made up of K measurements at once 11/13/2018

15 Beam Models of Range Finders
most range finders have a minimum and maximum range we seek a model that can represent the correct range measurement with noise unexpected obstacles failures random measurements 1 3 2 11/13/2018

16 Beam Models of Range Finders
Correct Measurement with Noise suppose that the beam intersects an obstacle at a range of model this measurement as a narrow Gaussian with mean 11/13/2018

17 Beam Models of Range Finders
Unexpected Obstacles in a dynamic environment there will be obstacles not found on a static map; these obstacles will cause range measurements shorter than expected if such obstacles appear continuously and independently at a constant average rate then they can be modeled as a Poisson process the time between events in a Poisson process has an exponential distribution with probability density function 11/13/2018

18 Beam Models of Range Finders
11/13/2018

19 Beam Models of Range Finders
Failures range finders can fail to sense an obstacle in which case most sensors return modeled as a point mass distribution centered at 11/13/2018

20 Beam Models of Range Finders
Random Measurements unexplainable measurements are modeled as a uniform distribution over the range [0, ] 11/13/2018

21 Beam Models of Range Finders
the complete model is a weighted sum of the previous four densities with weights 11/13/2018


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